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Results 1 - 10
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9,634
Input Representations (Inside the Mind and Out
- In G. Garding and M. Tsujimura (Eds.) WCCFL 22: Proceedings of the 22nd West Coast Conference on Formal Linguistics
, 2003
"... Young children’s productions of the words that they know often differ from adult productions of the same words in ways that traditionally have been described as feature substitutions or segment deletions. This is illustrated in the table in (1), which gives transcriptions of several of the ..."
Abstract
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Cited by 6 (2 self)
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Young children’s productions of the words that they know often differ from adult productions of the same words in ways that traditionally have been described as feature substitutions or segment deletions. This is illustrated in the table in (1), which gives transcriptions of several of the
Rapidly Estimating the Quality of Input Representations for Neural Networks
, 1995
"... The choice of an input representation for machine learning can have a profound impact on the accuracy of the learned model in classifying novel instances. A reliable method of rapidly estimating the value of a representation, independent of the learner, would be a powerful tool in the search for bet ..."
Abstract
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Cited by 7 (0 self)
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The choice of an input representation for machine learning can have a profound impact on the accuracy of the learned model in classifying novel instances. A reliable method of rapidly estimating the value of a representation, independent of the learner, would be a powerful tool in the search
Rapid Quality Estimation of Neural Network Input Representations
- Advances in Neural Information Processing Systems
, 1996
"... The choice of an input representation for a neural network can have a profound impact on its accuracy in classifying novel instances. However, neural networks are typically computationally expensive to train, making it difficult to test large numbers of alternative representations. This paper introd ..."
Abstract
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Cited by 6 (2 self)
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The choice of an input representation for a neural network can have a profound impact on its accuracy in classifying novel instances. However, neural networks are typically computationally expensive to train, making it difficult to test large numbers of alternative representations. This paper
Large margin methods for structured and interdependent output variables
- JOURNAL OF MACHINE LEARNING RESEARCH
, 2005
"... Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses the complementary ..."
Abstract
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Cited by 624 (12 self)
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Learning general functional dependencies between arbitrary input and output spaces is one of the key challenges in computational intelligence. While recent progress in machine learning has mainly focused on designing flexible and powerful input representations, this paper addresses
Shiftable Multi-scale Transforms
, 1992
"... Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal. Wavel ..."
Abstract
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Cited by 562 (36 self)
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Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal
Hierarchical Models of Object Recognition in Cortex
, 1999
"... The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore th ..."
Abstract
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Cited by 836 (84 self)
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The classical model of visual processing in cortex is a hierarchy of increasingly sophisticated representations, extending in a natural way the model of simple to complex cells of Hubel and Wiesel. Somewhat surprisingly, little quantitative modeling has been done in the last 15 years to explore
Greed is Good: Algorithmic Results for Sparse Approximation
, 2004
"... This article presents new results on using a greedy algorithm, orthogonal matching pursuit (OMP), to solve the sparse approximation problem over redundant dictionaries. It provides a sufficient condition under which both OMP and Donoho’s basis pursuit (BP) paradigm can recover the optimal representa ..."
Abstract
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Cited by 916 (9 self)
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representation of an exactly sparse signal. It leverages this theory to show that both OMP and BP succeed for every sparse input signal from a wide class of dictionaries. These quasi-incoherent dictionaries offer a natural generalization of incoherent dictionaries, and the cumulative coherence function
Analysis of Recommendation Algorithms for E-Commerce
, 2000
"... Recommender systems apply statistical and knowledge discovery techniques to the problem of making product recommendations during a live customer interaction and they are achieving widespread success in E-Commerce nowadays. In this paper, we investigate several techniques for analyzing large-scale pu ..."
Abstract
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Cited by 523 (22 self)
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the web-purchasing transaction of a large E-commerce company whereas the second data set was collected from MovieLens movie recommendation site. For the experimental purpose, we divide the recommendation generation process into three sub processes{ representation of input data, neighborhood formation
A distributed, developmental model of word recognition and naming
- PSYCHOLOGICAL REVIEW
, 1989
"... A parallel distributed processing model of visual word recognition and pronunciation is described. The model consists of sets of orthographic and phonological units and an interlevel of hidden units. Weights on connections between units were modified during a training phase using the back-propagatio ..."
Abstract
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Cited by 706 (49 self)
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is simulated without pronunciation rules, and lexical decisions are simulated without accessing word-level representations. The performance of the model is largely determined by three factors: the nature of the input, a significant fragment of written English; the learning rule, which encodes the implicit
Recognition-by-components: A theory of human image understanding
- Psychological Review
, 1987
"... The perceptual recognition of objects is conceptualized to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components, such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed theory, recog ..."
Abstract
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Cited by 1272 (23 self)
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The perceptual recognition of objects is conceptualized to be a process in which the image of the input is segmented at regions of deep concavity into an arrangement of simple geometric components, such as blocks, cylinders, wedges, and cones. The fundamental assumption of the proposed theory
Results 1 - 10
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9,634
